CN115081270B - Method, device, equipment and medium for predicting and evaluating environmental noise of rail transit - Google Patents
Method, device, equipment and medium for predicting and evaluating environmental noise of rail transit Download PDFInfo
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Abstract
The invention provides a method, a device, equipment and a medium for predicting and evaluating environmental noise of rail transit, which relate to the technical field of noise prediction and comprise the steps of obtaining first information and a wheel set-rail coupling prediction mathematical model; calculating according to the first information and a wheel set-track coupling prediction mathematical model to obtain an interaction force, wherein the interaction force is the interaction force of a wheel set and a track at a wheel track contact point under a moving condition; calculating to obtain wheel set sound power according to the interaction force of the movable wheel track and a preset wheel set vibration noise prediction model; according to the interaction force of the movable wheel rail and a preset rail vibration noise prediction model, calculating to obtain rail sound power; and according to the interaction force of the movable wheel track, the wheel set sound power, the track sound power and the preset sound pressure superposition mathematical model, calculating to obtain a predicted noise value. According to the method, the wheel track noise of the rail traffic can be calculated by establishing a new wheel track noise prediction model, and the calculation result is accurate, so that the method is beneficial to engineering application.
Description
Technical Field
The invention relates to the technical field of noise prediction, in particular to a method, a device, equipment and a medium for predicting and evaluating environmental noise of rail transit.
Background
In recent years, in order to optimally adjust urban layout and promote economic development of adjacent urban rings, urban rail transit is rapidly developed in China. As the speed of train operation increases, movement of the train has a significant impact on wheel track noise generation and propagation. The existing wheel track noise prediction method is mainly based on TWINS theory, but the theory avoids the problem of moving load, calculation is greatly simplified in both time domain and frequency domain, when the speed of the vehicle is lower than 160km/h, a reasonable result can be obtained, and when the speed of the vehicle is higher, a larger error exists in the calculation result of the method.
Disclosure of Invention
The invention aims to provide a method, a device, equipment and a readable storage medium for predicting and evaluating environmental noise of rail transit, so as to solve the problems. In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
in a first aspect, the present application provides a method for predicting and evaluating environmental noise of rail transit, including: acquiring first information and a wheel set-track coupling prediction mathematical model, wherein the first information comprises vehicle parameters, wheel set parameters and track parameters; calculating to obtain an interaction force according to the first information and the wheel set-track coupling prediction mathematical model, wherein the interaction force is the interaction force of a wheel set and a track at a wheel track contact point under a moving condition; according to the interaction force of the movable wheel track and a preset wheel set vibration noise prediction model, calculating to obtain wheel set sound power, wherein the wheel set sound power is the sound power of the wheel set on a rim, a radial plate and a wheel shaft structure; according to the interaction force of the movable wheel rail and a preset rail vibration noise prediction model, calculating to obtain rail sound power, wherein the rail sound power is rail radiation sound power taking a rail plate and a vehicle body as acoustic boundaries; and calculating to obtain a predicted noise value according to the interaction force of the movable wheel track, the wheel set sound power, the track sound power and a preset sound pressure superposition mathematical model.
In a second aspect, the present application further provides an apparatus for predicting and evaluating environmental noise of rail transit, including: the data acquisition module is used for acquiring first information and a wheel set-track coupling prediction mathematical model, wherein the first information comprises vehicle parameters, wheel set parameters and track parameters; the first calculation module is used for calculating and obtaining interaction force according to the first information and the wheel set-track coupling prediction mathematical model, wherein the interaction force is the interaction force of a wheel set and a track at a wheel track contact point under a moving condition; the second calculation module is used for calculating wheel set sound power according to the interaction force of the movable wheel track and a preset wheel set vibration noise prediction model, wherein the wheel set sound power is the sound power of the wheel set on a rim, a wheel disc and a wheel shaft structure; the third calculation module is used for calculating track sound power according to the interaction force of the movable wheel rail and a preset track vibration noise prediction model, wherein the track sound power is track radiation sound power taking a track plate and a vehicle body as acoustic boundaries; and the fourth calculation module is used for calculating and obtaining a predicted noise value according to the interaction force of the movable wheel track, the wheel set sound power, the track sound power and a preset sound pressure superposition mathematical model.
In a third aspect, the present application further provides an apparatus for predicting and evaluating environmental noise of rail transit, including:
a memory for storing a computer program;
and the processor is used for realizing the steps of the method for predicting and evaluating the environmental noise of the rail transit when executing the computer program.
In a fourth aspect, the present application also provides a readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method for predicting and evaluating environmental noise based on rail transit described above.
The beneficial effects of the invention are as follows:
the invention can calculate the wheel track noise of the rapid track traffic by establishing the new wheel track noise prediction model, has high realization degree and accurate calculation result, and is beneficial to engineering application.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the embodiments of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method for predicting and evaluating environmental noise of rail transit according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a device for predicting and evaluating environmental noise of rail transit according to an embodiment of the present invention;
fig. 3 is a schematic diagram of an apparatus for predicting and evaluating environmental noise of rail transit according to an embodiment of the present invention.
The marks in the figure: 1. a data acquisition module; 2. a first computing module; 21. a first calculation unit; 22. a second calculation unit; 23. a third calculation unit; 3. a second computing module; 31. a fourth calculation unit; 32. a fifth calculation unit; 33. a sixth calculation unit; 34. a seventh calculation unit; 4. a third calculation module; 41. an eighth calculation unit; 42. a ninth calculation unit; 43. a tenth calculation unit; 44. an eleventh calculation unit; 5. a third calculation module; 51. a twelfth calculation unit; 52. a thirteenth calculation unit; 521. a fourteenth calculation unit; 522. a fifteenth calculation unit; 801. a processor; 802. a memory; 803. a multimedia component; 804. an I/O interface; 805. a communication component.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures. Meanwhile, in the description of the present invention, the terms "first", "second", and the like are used only to distinguish the description, and are not to be construed as indicating or implying relative importance.
Example 1:
the embodiment provides a method for predicting and evaluating environmental noise of rail transit.
Referring to fig. 1, the method is shown to include steps S100, S200, S300, S400, and S500.
S100, acquiring first information and a wheel set-track coupling prediction mathematical model, wherein the first information comprises vehicle parameters, wheel set parameters and track parameters.
In step S100, the vehicle parameter, the wheel set parameter, and the track parameter refer to values of various variables in the track interval to be measured, including a vehicle mass, a vehicle running speed, a number of wheel sets, a wheel set diameter, a track density, a track elastic modulus, and the like.
And S200, calculating the interaction force according to the first information and the wheel set-track coupling prediction mathematical model, wherein the interaction force is the interaction force of the wheel set and the track at the wheel track contact point under the moving condition.
In step S200, the first information in the track interval to be measured is analyzed, and the obtained data is substituted into a preset wheel set-track coupling prediction mathematical model to calculate the interaction force, so that the design considers the moving load problem and more accurate data can be obtained.
And S300, calculating to obtain wheel set sound power according to the interaction force and a preset wheel set vibration noise prediction model, wherein the wheel set sound power is the sound power of the wheel set on the rim, the web and the wheel shaft structure.
In step S300, a wheel set vibration noise prediction model is established according to the axisymmetric characteristic and the axisymmetric acoustic boundary element method of the wheel set, and the wheel set acoustic power is calculated by using the interaction force as an input value. The wheel set vibration noise prediction model enables the accuracy of predicting the wheel set sound power to be higher by considering the bending vibration effect of the wheel shaft.
S400, calculating to obtain track sound power according to the interaction force and a preset track vibration noise prediction model, wherein the track sound power is track radiation sound power taking a track plate and a vehicle body as acoustic boundaries;
in step S400, the track plate and the support system are simulated, and a track vibration noise prediction model is built by combining 2.5 as an acoustic boundary element method, and the interaction force is used as an input value to calculate and obtain the track radiated sound power. Through reasonable model construction, the predicted value of the track radiated sound power is more accurate.
S500, calculating to obtain a predicted noise value according to the interaction force, the wheel set sound power, the track sound power and a preset sound pressure superposition mathematical model.
In step S500, the interaction force, the wheel set sound power and the track sound power calculated in the previous steps are substituted into the sound pressure superposition mathematical model, the sound power is converted into the sound pressure level and the sound pressure level is subjected to incoherent superposition to obtain the predicted noise value, and the obtained predicted noise value is more accurate through reasonable model design, thereby being beneficial to engineering application.
In the specific embodiment disclosed in the present application, step S200 includes step S210, step S220, and step S230.
And S210, calculating a first admittance, a second admittance, a wheel average roughness amplitude and a track average roughness amplitude according to the vehicle parameters, the wheel set parameters and the track parameters, wherein the first admittance comprises the vibration admittance of the moving wheel set at the wheel track contact point, and the second admittance comprises the vibration admittance of the steel rail at the wheel track contact point under the movement of the vehicle.
In step S210, the vehicle parameters, the wheel set parameters and the variables in the track parameters are extracted first, and the vibration admittance of the moving wheel set at the wheel track contact point and the vibration admittance of the track at the wheel track contact point in the coordinate system moving along with the vehicle are calculated; and then, according to the nominal rotation radius of the wheel set, the material parameters of the wheel tracks and the running speed of the vehicle, calculating to obtain the contact stiffness, the contact filtering range and the contact filtering amplitude between the wheel tracks. And calculating according to the wheel set irregularity amplitude and the track irregularity amplitude to obtain the wheel average roughness amplitude and the track average roughness amplitude.
And S220, calculating to obtain a wheel-rail combined roughness spectrum according to the wheel average roughness amplitude and the rail average roughness amplitude.
In step S220, the method for calculating the wheel-track joint roughness spectrum is as follows:
wherein Z is r (lambda) is the track average roughness amplitude, Z w (lambda) is the average roughness amplitude of the wheel set, both dimensions are m, each center wavelength can be alignedAt a wavenumber, the two amplitudes become Z r (β n ) And Z w (β n ) The wave number bandwidths corresponding to the two are respectively delta beta r And Δβ w . If interpolation is needed, the bandwidth after interpolation needs to be kept consistent and is delta beta 0 The two roughnesses are independent of each other. n is the nth center wave number.
S230, calculating to obtain interaction force according to the first admittance, the second admittance, the wheel-track combined roughness spectrum and a preset wheel pair-track coupling prediction mathematical model.
In step S230, a moving roughness method and a moving vehicle method are adopted, and simultaneously, a wheel set-rail coupling prediction mathematical model is constructed by taking into consideration the coupling of 4 wheel sets of two adjacent bogies on rails, the incoherence of the roughness of left and right wheel rails and the incoherence of the roughness of front and rear wheel rails. And taking the first admittance, the second admittance and the wheel track combined roughness spectrum as input values, solving a wheel pair-track coupling prediction mathematical model, and calculating to obtain the wheel track high-frequency interaction force.
In the specific embodiment disclosed in the present application, step S300 includes step S310, step S320, step S330 and step S340.
And S310, calculating to obtain the rigid body motion and the elastic deformation of the wheel set according to the interaction force and a preset rotating wheel set pair model.
In step S310, the vibration of the wheel set is circumferentially dispersed based on the fourier series according to the axisymmetric characteristic of the wheel set, and the gyroscopic effect and the centrifugal effect of the wheel set are considered, so that the elastic vibration and the rigid motion of the three-dimensional wheel set are obtained by combining the finite element method, the rigid motion comprises vertical, transverse, rotation, side rolling and head shaking, and the rotating wheel set is coupled with the train axle box, the first vertical steel spring, the first vertical shock absorber and the framework in the vertical direction.
S320, calculating to obtain the normal speed of the wheel pair surface according to the rigid motion and the elastic deformation.
In step S320, the finite element mesh of the two-dimensional section of the wheel set needs to meet the size requirement of 15mm on the wheel and the size requirement of 40mm on the wheel axle, the mesh type adopts 3-node and 4-node units, and 0-8-order pitch diameters need to be superimposed on the ring direction. The normal speed of the surface of the wheel set under each annular coefficient m (the absolute value of the annular coefficient is the pitch diameter) is as follows:
wherein, the liquid crystal display device comprises a liquid crystal display device,
for rigid body movement of wheel sets>
For elastic deformation of the wheel set, α is the circumferential angle of the wheel set, and i is an imaginary symbol.
S330, calculating the node sound pressure of the wheel pair surface according to the normal speed of the wheel pair surface.
It should be noted that, in step S330, the node sound pressure of the wheel pair surface is obtained by solving an axisymmetric acoustic integral equation, which is a common method in the art and is not described in detail in the present application.
And S340, calculating the wheel set sound power according to the wheel set surface node sound pressure and a preset sound radiation mathematical model.
In step S340, the acoustic power of the wheel set on the rim, the web and the axle structure is obtained by using the axisymmetric acoustic boundary element method. The acoustic grid and the finite element grid of the wheel set surface are partially overlapped, and the grid type is 3 node units. According to the radiated sound power of the wheel set, the wheel set sound source is equivalent to a monopole or a two-stage sub-sound source with the same energy, and the contribution of the sound source to the external field point of the vehicle under high-speed movement is predicted by combining a boundary element method. The acoustic radiation calculation formula is:
wherein, the liquid crystal display device comprises a liquid crystal display device,
the surface normal velocity is an input variable for the wheel pair surface node sound pressure under each circumferential coefficient.
In the specific embodiment disclosed in the present application, step S400 includes steps S410, S420, S430 and step S440.
And S410, calculating the sound pressure of the track node according to the interaction force.
In step S410, the track node sound pressure is calculated according to the high-frequency interaction force between the wheel tracks and the 2.5-dimensional acoustic integral equation.
S420, calculating to obtain the track vibration response according to the interaction force and a preset track sound vibration mathematical model.
In step S420, the track is constructed as an infinitely long periodic track acoustic vibration mathematical model, which includes a coupled vibration system of rail-fastener-track slab-CA mortar/self-compacting concrete/steel spring/rubber, in which the rail is modeled as an infinitely long iron-wood corbel, the fastener is modeled as a discrete support spring with a structural loss factor, the track slab is modeled using the thin plate theory, the under-slab support is a discrete steel spring or rubber block, the under-slab support is considered as a discrete supported spring with a structural loss factor, and the under-slab support is considered as a continuous supported spring with a structural loss factor, if it is a CA mortar/self-compacting concrete/vibration isolator. The vibration response calculation formula of the track is as follows:
β 0 ＝2π/L
Ω 0 ＝2πc/L
βp＝β+pβ 0
c is the running speed, p is the period coefficient, L is the length of the track plate, D is the D-th wheel set, D is the wheel set, beta is the wave number, and x 0 Is the coordinate of the zero point, omega is the excitation circle frequency, p is the wheel track force,
the vibration parameters of the steel rail under different wave numbers are shown, and alpha is the circumferential angle of the wheel set.
S430, calculating to obtain the normal speed vector of the track according to the vibration response of the track.
In step S430, the calculated track vibration response is projected onto the normal direction of the node to calculate a track normal velocity vector.
S440, calculating to obtain the track sound power according to the track node sound pressure, the track normal speed vector and a preset track vibration noise prediction model.
In step S440, a 2.5-dimensional acoustic boundary element method is adopted, a rigid boundary of the track board and a rigid boundary of the vehicle body are used as acoustic boundaries to construct a track vibration noise prediction model, a cross section boundary element grid of the track meets the size requirement of 15mm, a system consisting of the track board and a support thereof needs to consider modes below 2000Hz, the calculation frequency needs to reach 800Hz, and the calculation formula is as follows:
wherein the superscript x represents the conjugate, Γ is the two-dimensional acoustic boundary, Φ (y, z) is the lattice function matrix,
and->
The sound pressure of the orbit node and the normal velocity vector of the orbit acoustic boundary surface at different wave numbers beta and different circle frequencies omega are respectively.
In the specific embodiment disclosed in the present application, step S500 includes step S510 and step S520.
S510, calculating to obtain a wheel set sound pressure level and a track sound pressure level according to the wheel set sound power, the track sound power and the preset sound radiation equivalent conversion mathematical model, wherein the wheel set sound pressure level is the sound pressure level of wheel set radiation noise to the external field point of the vehicle, and the track sound pressure level is the sound pressure level of the external field point of the track vehicle.
In step S510, the wheel set sound power and the track sound power are equivalent to the dipole and monopole point sound sources having the same sound power, and the sound field established by the 2.5-dimensional acoustic boundary element is placed into the sound field, which includes the acoustic barrier, the concrete retaining wall, and the acoustic boundary of the surface of the earth, and the wheel set sound pressure level and the track sound pressure level are calculated.
S520, calculating to obtain a predicted noise value according to the interaction force, the wheel set sound pressure level, the orbit sound pressure level and a preset sound pressure superposition mathematical model.
In step S520, the wheel set sound pressure level and the track sound pressure level are superimposed to be the predicted noise values by incoherent superposition, taking into consideration the noise contribution of the wheel set and the track in the case of the interaction force.
In the specific embodiment disclosed in the present application, step S520 includes step S521, step S522, and step S523.
S521, calculating to obtain wheel set noise contribution according to the interaction force and the wheel set sound pressure level;
in step S521, a wheel set noise contribution mathematical model is created in consideration of the number of wheel sets in the train, radial vibration and axial vibration of the wheel sets, the upper structure of the wheel sets, and the like, and the wheel set noise contribution is obtained by bringing the interaction force and the wheel set sound pressure level into.
S522, calculating to obtain track noise contribution according to the interaction force and the track sound pressure level;
in step S522, a mathematical model of the track noise contribution is created in consideration of the vertical and horizontal coupling between the wheel and the rail, the incoherence of the roughness between the left and right rails, and the like, and the track noise contribution is calculated by substituting the interaction force and the track sound pressure level.
S523, calculating to obtain a predicted noise value according to the wheel set noise contribution, the track noise contribution and a preset sound pressure superposition mathematical model.
In step S522, the acoustic radiation of the wheel set and the track needs to be simplified into a point acoustic source without phase information, and the noise contributions of different wheel-track forces are non-coherent superimposed. In addition, because the distance between the uplink and the downlink is relatively short, when the 1h equivalent A sound level is adopted to evaluate the environmental noise, the influence of the far-side line is also required to be considered, and because the roughness of the two lines are mutually incoherent, the incoherent superposition is adopted to obtain the predicted noise value. The superposition formula is:
the upper mark W is wheel set noise contribution, the upper mark R is track noise contribution, the lower mark i represents ith wheel track force, and Nw is the number of wheel sets of the train. The design establishes a new noise prediction model by considering the moving effect of the load, the periodical dynamic excitation received by the wheel set when passing through the track, the bending vibration of the wheel axle and the like, realizes the accurate prediction of the wheel track noise of the rapid track traffic, and is beneficial to engineering application.
Example 2:
as shown in fig. 2, the present embodiment provides a track traffic environmental noise prediction and assessment device, which includes
The data acquisition module 1 is used for acquiring first information and a wheel set-track coupling prediction mathematical model, wherein the first information comprises vehicle parameters, wheel set parameters and track parameters.
The first calculation module 2 is configured to calculate an interaction force according to the first information and the wheel set-track coupling prediction mathematical model, where the interaction force is an interaction force of the wheel set and the track at the wheel track contact point under the moving condition.
And the second calculation module 3 is used for calculating the wheel set acoustic power according to the interaction force and a preset wheel set vibration noise prediction model, wherein the wheel set acoustic power is the acoustic power of the wheel set on the rim, the web and the wheel shaft structure.
And the third calculation module 4 is used for calculating the track sound power according to the interaction force and a preset track vibration noise prediction model, wherein the track sound power is track radiation sound power taking the track plate and the vehicle body as acoustic boundaries.
And the fourth calculation module 5 is used for calculating and obtaining a predicted noise value according to the interaction force, the wheel set sound power, the track sound power and the preset sound pressure superposition mathematical model.
In some specific embodiments, the second computing module 2 comprises:
the first calculating unit 21 is configured to calculate, according to the vehicle parameter, the wheel set parameter, and the track parameter, a first admittance including a vibration admittance of the moving wheel set at the wheel-rail contact point, a second admittance including a vibration admittance of the lower rail of the vehicle at the wheel-rail contact point, a wheel average roughness magnitude, and a track average roughness magnitude.
A second calculating unit 22 is configured to calculate a wheel-rail joint roughness spectrum according to the wheel average roughness amplitude and the track average roughness amplitude.
And a third calculation unit 23, configured to calculate and obtain the wheel-rail interaction force according to the first admittance, the second admittance, the wheel-rail combined roughness spectrum and a preset wheel-pair-rail coupling prediction mathematical model.
In some specific embodiments, the second computing module 3 comprises:
and a fourth calculation unit 31 for calculating the rigid body motion and the elastic deformation of the wheel set according to the interaction force of the moving wheel rail and the preset rotating wheel set pair model.
And a fifth calculation unit 32 for calculating the normal speed of the wheel pair surface according to the rigid motion and the elastic deformation.
And a sixth calculation unit 33, configured to calculate the wheel pair surface node sound pressure according to the wheel pair surface normal speed.
And a seventh calculation unit 34, configured to calculate the wheel set acoustic power according to the wheel set node sound pressure and a preset acoustic radiation mathematical model.
In some specific embodiments, the third computing module 4 comprises:
an eighth calculating unit 41 is configured to calculate the track node sound pressure according to the interaction force.
And a ninth calculation unit 42, configured to calculate the track vibration response according to the interaction force and a preset track acoustic vibration mathematical model.
A tenth calculation unit 43 for calculating a track normal velocity vector from the track vibration response.
The eleventh calculating unit 44 is configured to calculate the orbital acoustic power according to the orbital node sound pressure, the normal velocity vector of the orbit, and a preset orbital vibration noise prediction model.
In some specific embodiments, the fourth computing module 5 comprises:
the twelfth calculation unit 51 is configured to calculate, according to the equivalent conversion mathematical model of the wheel set sound power, the track sound power and the preset sound radiation, a wheel set sound pressure level and a track sound pressure level, where the wheel set sound pressure level is a sound pressure level of wheel set radiation noise to a vehicle external field point, and the track sound pressure level is a sound pressure level of the track to the vehicle external field point.
The thirteenth calculation unit 52 is configured to calculate a predicted noise value according to the interaction force, the wheel set sound pressure level, the track sound pressure level, and the preset sound pressure superposition mathematical model.
In some specific embodiments, thirteenth computing unit 52 includes:
a fourteenth calculating unit 521, configured to calculate a wheel set noise contribution according to the interaction force and the wheel set sound pressure level.
A fifteenth calculation unit 522 is configured to calculate a track noise contribution according to the interaction force and the track sound pressure level.
The sixteenth calculating unit 523 is configured to calculate a predicted noise value according to the wheel set noise contribution, the track noise contribution, and a preset sound pressure superposition mathematical model.
It should be noted that, regarding the apparatus in the above embodiments, the specific manner in which the respective modules perform the operations has been described in detail in the embodiments regarding the method, and will not be described in detail herein.
Example 3:
corresponding to the above method embodiment, there is further provided a rail transit environmental noise prediction evaluation device, which is described below and a rail transit environmental noise prediction evaluation method described above can be referred to correspondingly to each other.
Fig. 3 is a block diagram of a rail transit ambient noise prediction evaluation device 800, shown in accordance with an exemplary embodiment. As shown in fig. 3, the rail transit environmental noise prediction estimation device 800 may include: a processor 801, a memory 802. The rail transit ambient noise prediction assessment device 800 can also include one or more of a multimedia component 803, an i/O interface 804, and a communication component 805.
The processor 801 is configured to control the overall operation of the rail transit environmental noise prediction estimation device 800, so as to complete all or part of the steps in the rail transit environmental noise prediction estimation method. The memory 802 is used to store various types of data to support operation at the rail transit ambient noise prediction assessment device 800, which may include, for example, instructions for any application or method operating on the rail transit ambient noise prediction assessment device 800, as well as application-related data, such as contact data, transceived messages, pictures, audio, video, and the like. The Memory 802 may be implemented by any type or combination of volatile or non-volatile Memory devices, such as static random access Memory (Static Random Access Memory, SRAM for short), electrically erasable programmable Read-Only Memory (Electrically Erasable Programmable Read-Only Memory, EEPROM for short), erasable programmable Read-Only Memory (Erasable Programmable Read-Only Memory, EPROM for short), programmable Read-Only Memory (Programmable Read-Only Memory, PROM for short), read-Only Memory (ROM for short), magnetic Memory, flash Memory, magnetic disk, or optical disk. The multimedia component 803 may include a screen and an audio component. Wherein the screen may be, for example, a touch screen, the audio component being for outputting and/or inputting audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signals may be further stored in the memory 802 or transmitted through the communication component 805. The audio assembly further comprises at least one speaker for outputting audio signals. The I/O interface 804 provides an interface between the processor 801 and other interface modules, which may be a keyboard, mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 805 is configured to perform wired or wireless communication between the rail transit environmental noise prediction estimation device 800 and other devices. Wireless communication, such as Wi-Fi, bluetooth, near field communication (Near FieldCommunication, NFC for short), 2G, 3G or 4G, or a combination of one or more thereof, the respective communication component 805 may thus comprise: wi-Fi module, bluetooth module, NFC module.
In an exemplary embodiment, the rail transit environmental noise prediction estimation device 800 may be implemented by one or more application specific integrated circuits (Appl ication Specific Integrated Circuit, abbreviated as ASIC), digital signal processors (DigitalSignal Processor, abbreviated as DSP), digital signal processing devices (Digital Signal Processing Device, abbreviated as DSPD), programmable logic devices (Programmable Logic Device, abbreviated as PLD), field programmable gate arrays (Field Programmable Gate Array, abbreviated as FPGA), controllers, microcontrollers, microprocessors, or other electronic components for performing the rail transit environmental noise prediction estimation method described above.
In another exemplary embodiment, a computer readable storage medium is also provided, comprising program instructions which, when executed by a processor, implement the steps of the rail transit ambient noise prediction assessment method described above. For example, the computer readable storage medium may be the memory 802 described above including program instructions executable by the processor 801 of the rail transit environmental noise prediction estimation device 800 to perform the rail transit environmental noise prediction estimation method described above.
Example 4:
corresponding to the above method embodiment, there is further provided a readable storage medium in this embodiment, and a readable storage medium described below and a rail transit environmental noise prediction estimation method described above may be referred to correspondingly with each other.
A readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps of the rail transit environmental noise prediction estimation method of the above method embodiment.
The readable storage medium may be a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, and the like.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (8)
1. A method for predictive assessment of environmental noise in rail transit, comprising:
acquiring first information and a wheel set-track coupling prediction mathematical model, wherein the first information comprises vehicle parameters, wheel set parameters and track parameters;
calculating to obtain an interaction force according to the first information and the wheel set-track coupling prediction mathematical model, wherein the interaction force is the interaction force of a wheel set and a track at a wheel track contact point under a moving condition;
according to the interaction force and a preset wheel set vibration noise prediction model, calculating to obtain wheel set sound power, wherein the wheel set sound power is the sound power of the wheel set on a rim, a wheel disc and a wheel shaft structure;
according to the interaction force and a preset track vibration noise prediction model, calculating to obtain track sound power, wherein the track sound power is track radiation sound power taking a track plate and a vehicle body as acoustic boundaries;
according to the interaction force, the wheel set sound power, the track sound power and a preset sound pressure superposition mathematical model, calculating to obtain a predicted noise value;
wherein, the interaction force is calculated according to the first information and the wheel set-track coupling prediction mathematical model, and the method comprises the following steps:
calculating first admittance, second admittance, wheel average roughness amplitude and track average roughness amplitude according to the vehicle parameters, wheel set parameters and track parameters, wherein the first admittance comprises the vibration admittance of a moving wheel set at a wheel track contact point, and the second admittance comprises the vibration admittance of a steel rail under the movement of the vehicle at the wheel track contact point;
calculating according to the wheel average roughness amplitude and the track average roughness amplitude to obtain a wheel-track combined roughness spectrum;
and calculating to obtain interaction force according to the first admittance, the second admittance, the wheel-track combined roughness spectrum and a preset wheel-pair-track coupling prediction mathematical model.
2. The method for predicting and evaluating the environmental noise of the rail transit according to claim 1, wherein the calculating the wheel set sound power according to the interaction force and the preset wheel set vibration noise prediction model comprises:
calculating according to the interaction force and a preset rotating wheel pair data model to obtain rigid body motion and elastic deformation of the wheel pair;
calculating to obtain the normal speed of the wheel pair surface according to the rigid motion and the elastic deformation;
calculating according to the normal speed of the wheel pair surface to obtain the node sound pressure of the wheel pair surface;
and calculating according to the wheel pair surface node sound pressure and a preset sound radiation mathematical model to obtain wheel pair sound power.
3. The method for predicting and evaluating the environmental noise of the rail transit according to claim 1, wherein the calculating the predicted noise value according to the interaction force, the wheel set sound power, the rail sound power and the preset sound pressure superposition mathematical model comprises:
calculating to obtain a wheel set sound pressure level and a track sound pressure level according to the wheel set sound power, the track sound power and a preset sound radiation equivalent conversion mathematical model, wherein the wheel set sound pressure level is the sound pressure level of wheel set radiation noise to a vehicle external field point, and the track sound pressure level is the sound pressure level of the track to the vehicle external field point;
and calculating to obtain a predicted noise value according to the interaction force, the wheel set sound pressure level, the orbit sound pressure level and a preset sound pressure superposition mathematical model.
4. An apparatus for predictive assessment of environmental noise in rail transit, comprising:
the data acquisition module is used for acquiring first information and a wheel set-track coupling prediction mathematical model, wherein the first information comprises vehicle parameters, wheel set parameters and track parameters;
the first calculation module is used for calculating and obtaining interaction force according to the first information and the wheel set-track coupling prediction mathematical model, wherein the interaction force is the interaction force of a wheel set and a track at a wheel track contact point under a moving condition;
the second calculation module is used for calculating and obtaining wheel set sound power according to the interaction force and a preset wheel set vibration noise prediction model, wherein the wheel set sound power is the sound power of the wheel set on the wheel rim, the wheel disc and the wheel shaft structure;
the third calculation module is used for calculating track sound power according to the interaction force and a preset track vibration noise prediction model, wherein the track sound power is track radiation sound power taking a track plate and a vehicle body as acoustic boundaries;
the fourth calculation module is used for calculating to obtain a predicted noise value according to the interaction force, the wheel set sound power, the track sound power and a preset sound pressure superposition mathematical model;
wherein the first computing module comprises:
the first calculation unit is used for calculating first admittance, second admittance, wheel average roughness amplitude and track average roughness amplitude according to the vehicle parameters, wheel set parameters and track parameters, wherein the first admittance comprises the vibration admittance of the moving wheel set at the wheel track contact point, and the second admittance comprises the vibration admittance of the steel rail at the wheel track contact point under the movement of the vehicle;
the second calculation unit is used for calculating and obtaining a wheel-rail combined roughness spectrum according to the wheel average roughness amplitude and the rail average roughness amplitude;
the third calculation unit is used for calculating and obtaining the wheel-rail interaction force according to the first admittance, the second admittance, the wheel-rail combined roughness spectrum and a preset wheel-pair-rail coupling prediction mathematical model.
5. The apparatus of claim 4, wherein the second computing module comprises:
the fourth calculation unit is used for calculating rigid body motion and elastic deformation of the wheel set according to the interaction force of the movable wheel rail and a preset rotating wheel set pair model;
a fifth calculation unit for calculating a wheel pair surface normal speed according to the rigid motion and the elastic deformation;
the sixth calculation unit is used for calculating the wheel pair surface node sound pressure according to the wheel pair surface normal speed;
and the seventh calculation unit is used for calculating the wheel set sound power according to the wheel set surface node sound pressure and a preset sound radiation mathematical model.
6. The apparatus for predictive evaluation of environmental noise in rail transit of claim 4, wherein the fourth computing module comprises:
a twelfth calculation unit, configured to calculate, according to the wheel set acoustic power, the track acoustic power, and the preset acoustic radiation equivalent conversion mathematical model, to obtain a wheel set acoustic pressure level and a track acoustic pressure level, where the wheel set acoustic pressure level is an acoustic pressure level of wheel set radiation noise to a vehicle external field point, and the track acoustic pressure level is an acoustic pressure level of the track to the vehicle external field point;
and a thirteenth calculation unit, configured to calculate a predicted noise value according to the interaction force, the wheel set sound pressure level, the track sound pressure level, and a preset sound pressure superposition mathematical model.
7. An apparatus for predictive assessment of environmental noise in rail transit, comprising:
a memory for storing a computer program;
a processor for implementing the steps of the method of rail transit environmental noise prediction assessment of any one of claims 1 to 3 when executing the computer program.
8. A readable storage medium, characterized by: a computer program stored on a readable storage medium, which when executed by a processor, implements the steps of the method of rail transit ambient noise prediction assessment according to any one of claims 1 to 3.
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